



'''simple docstring'''





from __future__ import annotations

import queue


class 					snake_case			:



       def __init__(					self  ,UpperCAmelCase_   )	->				List[Any]:
           lowercase__									=    data
           lowercase__									=    None
           lowercase__									=    None





def 							lowerCamelCase	(					):





    '''simple docstring'''


    print("\n********Press N to stop entering at any point of time********\n"							)
    lowercase__									=    input("Enter the value of the root node: "							).strip().lower()
    lowercase__									=    queue.Queue()
    lowercase__									=    TreeNode(int(_A							)							)
    q.put(_A							)
    while not q.empty():
        lowercase__									=    q.get()
        lowercase__									=    f'''Enter the left node of {node_found.data}: '''
        lowercase__									=    input(_A							).strip().lower() or "n"
        if check == "n":
            return tree_node
        lowercase__									=    TreeNode(int(_A							)							)
        lowercase__									=    left_node
        q.put(_A							)
        lowercase__									=    f'''Enter the right node of {node_found.data}: '''
        lowercase__									=    input(_A							).strip().lower() or "n"
        if check == "n":
            return tree_node
        lowercase__									=    TreeNode(int(_A							)							)
        lowercase__									=    right_node
        q.put(_A							)
    raise




def 							lowerCamelCase	(					_snake_case	:    TreeNode							):





    '''simple docstring'''


    if not isinstance(_A  ,_A							) or not node:
        return
    print(node.data  ,end=","							)
    pre_order(node.left							)
    pre_order(node.right							)




def 							lowerCamelCase	(					_snake_case	:    TreeNode							):





    '''simple docstring'''


    if not isinstance(_A  ,_A							) or not node:
        return
    in_order(node.left							)
    print(node.data  ,end=","							)
    in_order(node.right							)




def 							lowerCamelCase	(					_snake_case	:    TreeNode							):





    '''simple docstring'''


    if not isinstance(_A  ,_A							) or not node:
        return
    post_order(node.left							)
    post_order(node.right							)
    print(node.data  ,end=","							)




def 							lowerCamelCase	(					_snake_case	:    TreeNode							):





    '''simple docstring'''


    if not isinstance(_A  ,_A							) or not node:
        return
    lowercase__									=    queue.Queue()
    q.put(_A							)
    while not q.empty():
        lowercase__									=    q.get()
        print(node_dequeued.data  ,end=","							)
        if node_dequeued.left:
            q.put(node_dequeued.left							)
        if node_dequeued.right:
            q.put(node_dequeued.right							)




def 							lowerCamelCase	(					_snake_case	:    TreeNode							):





    '''simple docstring'''


    if not isinstance(_A  ,_A							) or not node:
        return
    lowercase__									=    queue.Queue()
    q.put(_A							)
    while not q.empty():
        lowercase__									=    []
        while not q.empty():
            lowercase__									=    q.get()
            print(node_dequeued.data  ,end=","							)
            if node_dequeued.left:
                list_.append(node_dequeued.left							)
            if node_dequeued.right:
                list_.append(node_dequeued.right							)
        print()
        for node in list_:
            q.put(_A							)




def 							lowerCamelCase	(					_snake_case	:    TreeNode							):





    '''simple docstring'''


    if not isinstance(_A  ,_A							) or not node:
        return
    lowercase__									=    []
    lowercase__									=    node
    while n or stack:
        while n:  # start from root node, find its left child
            print(n.data  ,end=","							)
            stack.append(_A							)
            lowercase__									=    n.left
        # end of while means current node doesn't have left child
        lowercase__									=    stack.pop()
        # start to traverse its right child
        lowercase__									=    n.right




def 							lowerCamelCase	(					_snake_case	:    TreeNode							):





    '''simple docstring'''


    if not isinstance(_A  ,_A							) or not node:
        return
    lowercase__									=    []
    lowercase__									=    node
    while n or stack:
        while n:
            stack.append(_A							)
            lowercase__									=    n.left
        lowercase__									=    stack.pop()
        print(n.data  ,end=","							)
        lowercase__									=    n.right




def 							lowerCamelCase	(					_snake_case	:    TreeNode							):





    '''simple docstring'''


    if not isinstance(_A  ,_A							) or not node:
        return
    lowercase__							,							lowercase__									=    [], []
    lowercase__									=    node
    stacka.append(_A							)
    while stacka:  # to find the reversed order of post order, store it in stack2
        lowercase__									=    stacka.pop()
        if n.left:
            stacka.append(n.left							)
        if n.right:
            stacka.append(n.right							)
        stacka.append(_A							)
    while stacka:  # pop up from stack2 will be the post order
        print(stacka.pop().data  ,end=","							)




def 							lowerCamelCase	(					_snake_case	:    str = ""  ,_snake_case	:    Optional[Any]=50  ,_snake_case	:    str="*"							):





    '''simple docstring'''


    if not s:
        return "\n" + width * char
    lowercase__							,							lowercase__									=    divmod(width - len(_A							) - 2  ,2							)
    return f'''{left * char} {s} {(left + extra) * char}'''


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(prompt("Binary Tree Traversals"))

 SCREAMING_SNAKE_CASE__          =  build_tree()
 print(prompt("Pre Order Traversal"))
 pre_order(node)
 print(prompt() + "\n")

 print(prompt("In Order Traversal"))
 in_order(node)
 print(prompt() + "\n")

 print(prompt("Post Order Traversal"))
 post_order(node)
 print(prompt() + "\n")

 print(prompt("Level Order Traversal"))
 level_order(node)
 print(prompt() + "\n")

 print(prompt("Actual Level Order Traversal"))
 level_order_actual(node)
 print("*" * 50 + "\n")

 print(prompt("Pre Order Traversal - Iteration Version"))
 pre_order_iter(node)
 print(prompt() + "\n")

 print(prompt("In Order Traversal - Iteration Version"))
 in_order_iter(node)
 print(prompt() + "\n")

 print(prompt("Post Order Traversal - Iteration Version"))
 post_order_iter(node)
 print(prompt())








import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors







@require_tokenizers
class 							lowerCamelCase__						(				UpperCAmelCase       ,						unittest.TestCase   ):






			"""simple docstring"""






			_UpperCamelCase		:       List[str] 			=		MvpTokenizer
			_UpperCamelCase		:       Any 			=		MvpTokenizerFast
			_UpperCamelCase		:       List[str] 			=		True
			_UpperCamelCase		:       Dict 			=		filter_roberta_detectors




			def 					snake_case__					(				self  ):

						'''simple docstring'''


						super().setUp()
						UpperCamelCase__       =							[
						    "l",
						    "o",
						    "w",
						    "e",
						    "r",
						    "s",
						    "t",
						    "i",
						    "d",
						    "n",
						    "\u0120",
						    "\u0120l",
						    "\u0120n",
						    "\u0120lo",
						    "\u0120low",
						    "er",
						    "\u0120lowest",
						    "\u0120newer",
						    "\u0120wider",
						    "<unk>",
						]
						UpperCamelCase__       =							dict(zip(snake_case   ,    range(len(snake_case  )  )  )  )
						UpperCamelCase__       =							["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
						UpperCamelCase__       =							{"unk_token": "<unk>"}

						UpperCamelCase__       =							os.path.join(self.tmpdirname   ,    VOCAB_FILES_NAMES["vocab_file"]  )
						UpperCamelCase__       =							os.path.join(self.tmpdirname   ,    VOCAB_FILES_NAMES["merges_file"]  )
						with open(self.vocab_file   ,    "w"   ,    encoding="utf-8"  ) as fp:
									fp.write(json.dumps(snake_case  ) + "\n"  )
						with open(self.merges_file   ,    "w"   ,    encoding="utf-8"  ) as fp:
									fp.write("\n".join(snake_case  )  )




			def 					snake_case__					(				self   ,    **snake_case  ):

						'''simple docstring'''


						kwargs.update(self.special_tokens_map  )
						return self.tokenizer_class.from_pretrained(self.tmpdirname   ,    **snake_case  )




			def 					snake_case__					(				self   ,    **snake_case  ):

						'''simple docstring'''


						kwargs.update(self.special_tokens_map  )
						return self.rust_tokenizer_class.from_pretrained(self.tmpdirname   ,    **snake_case  )




			def 					snake_case__					(				self   ,    snake_case  ):

						'''simple docstring'''


						return "lower newer", "lower newer"




			@cached_property
			def 					snake_case__					(				self  ):

						'''simple docstring'''


						return MvpTokenizer.from_pretrained("RUCAIBox/mvp"  )




			@cached_property
			def 					snake_case__					(				self  ):

						'''simple docstring'''


						return MvpTokenizerFast.from_pretrained("RUCAIBox/mvp"  )




			@require_torch
			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							["A long paragraph for summarization.", "Another paragraph for summarization."]
						UpperCamelCase__       =							[0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									UpperCamelCase__       =							tokenizer(snake_case   ,    max_length=len(snake_case  )   ,    padding=snake_case   ,    return_tensors="pt"  )
									self.assertIsInstance(snake_case   ,    snake_case  )

									self.assertEqual((2, 9)   ,    batch.input_ids.shape  )
									self.assertEqual((2, 9)   ,    batch.attention_mask.shape  )
									UpperCamelCase__       =							batch.input_ids.tolist()[0]
									self.assertListEqual(snake_case   ,    snake_case  )
									# Test that special tokens are reset




			@require_torch
			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							["A long paragraph for summarization.", "Another paragraph for summarization."]
						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									UpperCamelCase__       =							tokenizer(snake_case   ,    padding=snake_case   ,    return_tensors="pt"  )
									# check if input_ids are returned and no labels
									self.assertIn("input_ids"   ,    snake_case  )
									self.assertIn("attention_mask"   ,    snake_case  )
									self.assertNotIn("labels"   ,    snake_case  )
									self.assertNotIn("decoder_attention_mask"   ,    snake_case  )




			@require_torch
			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							[
						    "Summary of the text.",
						    "Another summary.",
						]
						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									UpperCamelCase__       =							tokenizer(text_target=snake_case   ,    max_length=32   ,    padding="max_length"   ,    return_tensors="pt"  )
									self.assertEqual(32   ,    targets["input_ids"].shape[1]  )




			@require_torch
			def 					snake_case__					(				self  ):

						'''simple docstring'''


						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									UpperCamelCase__       =							tokenizer(
									    ["I am a small frog" * 1024, "I am a small frog"]   ,    padding=snake_case   ,    truncation=snake_case   ,    return_tensors="pt"  )
									self.assertIsInstance(snake_case   ,    snake_case  )
									self.assertEqual(batch.input_ids.shape   ,    (2, 1024)  )




			@require_torch
			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							["A long paragraph for summarization."]
						UpperCamelCase__       =							[
						    "Summary of the text.",
						]
						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									UpperCamelCase__       =							tokenizer(snake_case   ,    text_target=snake_case   ,    return_tensors="pt"  )
									UpperCamelCase__       =							inputs["input_ids"]
									UpperCamelCase__       =							inputs["labels"]
									self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()  )
									self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()  )
									self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()  )
									self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()  )




			def 					snake_case__					(				self  ):

						'''simple docstring'''


						pass







			def 					snake_case__					(				self  ):

						'''simple docstring'''


						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
												UpperCamelCase__       =							self.rust_tokenizer_class.from_pretrained(snake_case   ,    **snake_case  )
												UpperCamelCase__       =							self.tokenizer_class.from_pretrained(snake_case   ,    **snake_case  )
												UpperCamelCase__       =							"A, <mask> AllenNLP sentence."
												UpperCamelCase__       =							tokenizer_r.encode_plus(snake_case   ,    add_special_tokens=snake_case   ,    return_token_type_ids=snake_case  )
												UpperCamelCase__       =							tokenizer_p.encode_plus(snake_case   ,    add_special_tokens=snake_case   ,    return_token_type_ids=snake_case  )

												# token_type_ids should put 0 everywhere
												self.assertEqual(sum(tokens_r["token_type_ids"]  )   ,    sum(tokens_p["token_type_ids"]  )  )

												# attention_mask should put 1 everywhere, so sum over length should be 1
												self.assertEqual(
												    sum(tokens_r["attention_mask"]  ) / len(tokens_r["attention_mask"]  )   ,    sum(tokens_p["attention_mask"]  ) / len(tokens_p["attention_mask"]  )   ,    )

												UpperCamelCase__       =							tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]  )
												UpperCamelCase__       =							tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"]  )

												# Rust correctly handles the space before the mask while python doesnt
												self.assertSequenceEqual(tokens_p["input_ids"]   ,    [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]  )
												self.assertSequenceEqual(tokens_r["input_ids"]   ,    [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]  )

												self.assertSequenceEqual(
												    snake_case   ,    ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]  )
												self.assertSequenceEqual(
												    snake_case   ,    ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]  )


